Datasets:
Tasks:
Token Classification
Languages:
Slovenian
Size:
1K - 10K
Tags:
metaphor-classification
metonymy-classification
metaphor-frame-classification
multiword-expression-detection
License:
Commit
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Update README.md
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README.md
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---
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---
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---
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annotations_creators:
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- expert-generated
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language:
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- sl
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language_creators:
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- found
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license:
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- cc-by-nc-sa-4.0
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multilinguality:
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- monolingual
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pretty_name: G-KOMET
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size_categories:
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- 1K<n<10K
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source_datasets: []
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tags:
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- metaphor detection
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- metonymy detection
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- spoken corpus
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- mip
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- mipvu
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task_categories:
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- token-classification
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task_ids:
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- token-classification-other-metaphor-classification
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- token-classification-other-metonymy-classification
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- token-classification-other-metaphor-frame-classification
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---
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# Dataset Card for G-KOMET
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### Dataset Summary
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G-KOMET 1.0 is a corpus of metaphorical expressions in spoken Slovene language, covering around 50,000 lexical units across 5695 sentences. The corpus contains samples from the Gos corpus of spoken Slovene and includes a balanced set of transcriptions of informative, educational, entertaining, private, and public discourse.
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It is also annotated with idioms and metonymies. Note that these are both annotated as metaphor types. This is different from the annotations in [KOMET](https://huggingface.co/datasets/cjvt/komet), where these are both considered a type of frame. We keep the data as untouched as possible and let the user decide how they want to handle this.
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### Supported Tasks and Leaderboards
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Metaphor detection, metonymy detection, metaphor type classification, metaphor frame classification.
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### Languages
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Slovenian.
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## Dataset Structure
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### Data Instances
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A sample instance from the dataset:
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```
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{
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'document_name': 'G-Komet001.xml',
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'idx': 3,
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'idx_paragraph': 0,
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'idx_sentence': 3,
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'sentence_words': ['no', 'zdaj', 'samo', 'še', 'za', 'eno', 'orientacijo'],
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'met_type': [
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{'type': 'MRWi', 'word_indices': [6]}
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],
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'met_frame': [
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{'type': 'spatial_orientation', 'word_indices': [6]}
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]
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}
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```
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The sentence comes from the document `G-Komet001.xml`, is the 3rd sentence in the document and is the 3rd sentence inside the 0th paragraph in the document.
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The word "orientacijo" is annotated as an indirect metaphor-related word (`MRWi`).
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It is also annotated with the frame "spatial_orientation".
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### Data Fields
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- `document_name`: a string containing the name of the document in which the sentence appears;
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- `idx`: a uint32 containing the index of the sentence inside its document;
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- `idx_paragraph`: a uint32 containing the index of the paragraph in which the sentence appears;
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- `idx_sentence`: a uint32 containing the index of the sentence inside its paragraph;
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containing the consecutive number of the paragraph inside the current news article;
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- `sentence_words`: words in the sentence;
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- `met_type`: metaphors in the sentence, marked by their type and word indices;
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- `met_frame`: metaphor frames in the sentence, marked by their type (frame name) and word indices.
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## Dataset Creation
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The corpus contains samples from the GOS corpus of spoken Slovene and includes a balanced set of transcriptions of informative, educational, entertaining, private, and public discourse. It contains hand-annotated metaphor-related words, i.e. linguistic expressions that have the potential for people to interpret them as metaphors, idioms, i.e. multi-word units in which at least one word has been used metaphorically, and metonymies, expressions that we use to express something else.
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For more information, please check out the paper (which is in Slovenian language) or contact the dataset author.
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## Additional Information
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### Dataset Curators
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Špela Antloga.
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### Licensing Information
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CC BY-NC-SA 4.0
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### Citation Information
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```
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@InProceedings{antloga2022gkomet,
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title = {Korpusni pristopi za identifikacijo metafore in metonimije: primer metonimije v korpusu gKOMET},
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author={Antloga, \v{S}pela},
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booktitle={Proceedings of the Conference on Language Technologies and Digital Humanities (Student papers)},
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year={2022},
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pages={271-277}
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}
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```
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### Contributions
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Thanks to [@matejklemen](https://github.com/matejklemen) for adding this dataset.
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